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.env

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+GOOGLE_API_KEY="AIzaSyBaMtbGoJFN2YfDqCOYlsw8S6RO_VISq18"

geminiAPIv2.py

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+from dotenv import load_dotenv
+load_dotenv()
+
+import os
+import google.generativeai as genai
+import gradio as gr
+
+# Configure Google Generative AI
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+model = genai.GenerativeModel("gemini-pro")
+
+def get_gemini_responces(message, chat_history):
+    # Assuming the message is a question for the Gemini model
+    responce = model.generate_content(message)
+    # Append the model's response to the chat history
+    chat_history.append((message, responce.text))
+    return "", chat_history
+
+# Define the Gradio interface with a Chatbot component
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.ClearButton([msg, chatbot])
+
+    msg.submit(get_gemini_responces, [msg, chatbot], [msg, chatbot])
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    demo.launch()